



'''simple docstring'''






def  lowerCamelCase__			(		_A = 10**9							):
  a		:   Dict	  =	1
  a		:   Union[str, Any]	  =	2

  a		:   Optional[int]	  =	0
  a		:   Tuple	  =	0
  a		:   List[str]	  =	0
  while perimeter <= max_perimeter:
    perimeters_sum += perimeter

    prev_value += 2 * value
    value += prev_value

    a		:   Union[str, Any]	  =	2 * value + 2 if i % 2 == 0 else 2 * value - 2
    i += 1

  return perimeters_sum


if __name__ == "__main__":
     print(F"{solution() = }")




'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowerCAmelCase:   List[str]					=		{
    'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCAmelCase:   str					=		[
         'FALCON_PRETRAINED_MODEL_ARCHIVE_LIST',
         'FalconForCausalLM',
         'FalconModel',
         'FalconPreTrainedModel',
         'FalconForSequenceClassification',
         'FalconForTokenClassification',
         'FalconForQuestionAnswering',
     ]


if TYPE_CHECKING:
     from .configuration_falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_falcon import (
              FALCON_PRETRAINED_MODEL_ARCHIVE_LIST,
              FalconForCausalLM,
              FalconForQuestionAnswering,
              FalconForSequenceClassification,
              FalconForTokenClassification,
              FalconModel,
              FalconPreTrainedModel,
          )


else:
     import sys

     lowerCAmelCase:   Optional[int]					=		_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)